Model-based Drug Development

Data analysis in PKPD studies is a specialised area of modelling that combines mathematical and statistical knowledge in data fitting with the sound knowledge of the human body as a system to enable choosing more mechanistic models. The analysis can describe the observed data but also it can be used for the purpose of prediction.

The mathematical background provided in this module relates to linear and non-linear fitting, optimisation procedures that are applied to objective function(s), optimal design issues. Statistical input relates to finding inferences, covariates, application of non-linear mixed effect modelling, and application of Bayesian or non-Bayesian methods amongst other subjects.

This Unit also provides information on available tools for data analysis and their applications. Many commonly used platforms for data analysis (such as WinNonlin and NONMEM) are part of the module. Students analyse data with different packages to grasp the advantages and disadvantages of these packages.

The total teaching and assessment methods would be based on 10 notional learning hours per credit (i.e. a total of 300 learning hours teaching and assessment for this 30-credit unit).

• Distinguish the capability of different tools to perform certain type of data analysis.

• Make informed choices on using various models to be used for fit data obtained from studies involving Enzyme Kinetics, Pharmacokinetics and Pharmacodynamics.
• Report essential part of the results from data analysis.

• Critically assess published reports in the field of Pharmacometrics for consistency in use of methods and other assumptions.